Systems and methods for prosthetic component orientation

ABSTRACT

A computer-implemented method determines an orientation parameter value of a prosthetic component. The method includes receiving a first desired separation distance between a tibial prosthetic component and a femoral prosthetic component at a first flexion position of a knee joint and estimating a first estimated separation distance between the tibial prosthetic component and the femoral prosthetic component at the first flexion position of the knee joint for at least one potential orientation of the femoral prosthetic component. The method also includes determining a first orientation parameter value of the femoral prosthetic component by comparing the first estimated separation distance to the first desired separation distance and outputting the first orientation parameter value via a user interface.

TECHNICAL FIELD

The present disclosure relates generally to prosthetic componentorientation systems and, more particularly, to systems for determiningan orientation of one or more prosthetic implants to be used in kneejoint replacement surgeries.

BACKGROUND

The knee joint includes the interface between the distal end of thefemur and the proximal end of the tibia. In a properly-functioning kneejoint, medial and lateral condyles of the femur pivot smoothly alongmenisci attached to respective medial and lateral condyles of the tibia.In certain knees, such as diseased arthritic knees, cartilage may haveeroded, causing the space between the femur and the tibia to collapseand leading to bone-on-bone contact. When this happens, the naturalbones and cartilage that form the joint may be unable to properlyarticulate, which can lead to joint pain and/or interfere with normaluse of the joint.

In some situations, surgery is required to correct the alignment betweenthe tibia and femur and restore normal use of the joint. Depending uponthe severity of the damage, the surgery may involve partially orcompletely replacing the joint with prosthetic components. During suchknee replacement procedures, a surgeon resects damaged portions of thebone and cartilage, while attempting to leave healthy tissue intact. Thesurgeon then fits the healthy tissue with artificial prostheticcomponents designed to replicate the resected tissue and restore properknee joint operation.

The orientation of these prosthetic components on the tibia and/or femurmay impact the alignment between the tibia and the femur and thus affecthow the joint articulates. Improperly oriented prosthetic components mayfail to restore proper knee joint operation and/or may cause prematurecomponent failure or deterioration, among other problems. Accordingly,proper orientation of these components is critical, and a surgeon mayspend a great deal of time and effort determining the properorientations of the prosthetic components before fitting them to thejoint. However, even with the surgeon's experience, making such adetermination manually may not result in an optimal, or even acceptable,location and orientation of the prosthetic components.

SUMMARY

According to one aspect, the present disclosure is directed to acomputer-implemented method for determining an orientation parametervalue of a prosthetic component. The method may include receiving afirst desired separation distance between a tibial prosthetic componentand a femoral prosthetic component at a first flexion position of a kneejoint, and estimating a first estimated separation distance between thetibial prosthetic component and the femoral prosthetic component at thefirst flexion position of the knee joint for at least one potentialorientation of the femoral prosthetic component. The method may alsoinclude determining a first orientation parameter value of the femoralprosthetic component by comparing the first estimated separationdistance to the first desired separation distance, and outputting thefirst orientation parameter value via a user interface.

According to another aspect, the present disclosure is directed to asystem for determining an orientation parameter value of a prostheticcomponent. The system may include an input device configured to receivea first desired separation distance between a tibial prostheticcomponent and a femoral prosthetic component at a first flexion positionof a knee joint. The system may also include a processor that isoperatively coupled to the input device. The processor may be configuredto estimate a first estimated separation distance between the tibialprosthetic component and the femoral prosthetic component at the firstflexion position of the knee joint for at least one potentialorientation of the femoral prosthetic component, and determine a firstorientation parameter value of the femoral prosthetic component bycomparing the first estimated separation distance to the first desiredseparation distance. The system may also include a display operativelycoupled to the processor and configured to output the first orientationparameter value.

According to another aspect, the present disclosure is directed toanother computer-implemented method for determining an orientation of aprosthetic component. The method may include recording relativepositions of a tibia and a femur at a plurality of flexion positions ofthe knee, and receiving a plurality of looseness values via a userinterface, each of the plurality of looseness values corresponding to alooseness preference between the tibia and the femur for one of theplurality of flexion positions of the knee. The method may also includedetermining an orientation of a prosthetic component for the knee basedon the recorded relative positions of the tibia and the femur and thereceived looseness values, and outputting the orientation of theprosthetic component via a display.

Additional objects and advantages of disclosed embodiments will be setforth in part in the description which follows, and in part will beobvious from the description, or may be learned by practice of thedisclosed embodiments. The objects and advantages of the disclosedembodiments will be realized and attained by means of the elements andcombinations particularly pointed out in the appended claims. It is tobe understood that both the foregoing general description and thefollowing detailed description are exemplary and explanatory only andare not restrictive of the disclosed embodiments, as claimed.

BRIEF DESCRIPTION OF THE DRAWINGS

The accompanying drawings, which are incorporated in and constitute apart of this specification, illustrate several embodiments that,together with the description, serve to explain the principles andfeatures of the present disclosure.

FIG. 1 illustrates a perspective view of post-operative prosthetic kneejoint fitted with prosthetic components, consistent with disclosedembodiments;

FIG. 2 is a schematic diagram of a computer system programmed todetermine prosthetic component orientation, consistent with disclosedembodiments

FIG. 3 illustrates side view of a knee joint at multiple differentflexion positions, consistent with disclosed embodiments;

FIG. 4 illustrates an exemplary user interface, consistent withdisclosed embodiments;

FIG. 5 is a pictorial illustration representing the relative positioningof a three-dimensional femoral prosthetic component model and athree-dimensional tibial prosthetic component model at multipledifferent flexion positions, consistent with certain disclosedembodiments;

FIG. 6 is a flowchart illustrating an exemplary process for determiningprosthetic component orientation, consistent with disclosed embodiments;and

FIG. 7 is a flowchart illustrating another exemplary process fordetermining prosthetic component orientation, consistent with disclosedembodiments.

DETAILED DESCRIPTION

Reference will now be made in detail to exemplary embodiments of thepresent disclosure, examples of which are illustrated in theaccompanying drawings.

FIG. 1 illustrates a perspective view of a post-operative prostheticknee joint 100 fitted with prosthetic components 110 and 120, consistentwith disclosed embodiments. Knee joint 100 includes a tibia 101 and afemur 102. Femur 102 may include a lateral condyle 103 and a medialcondyle 104 separated by an intercondylar notch 105. Tibia 101 maylikewise include a lateral condyle 106 and a medial condyle 107. Duringknee surgery, such as unicompartmental arthroplasty, prostheticcomponents may be fitted to one or more of lateral condyle 103, medialcondyle 104, lateral condyle 106, and medial condyle 107. For example,FIG. 1 illustrates a femoral prosthetic component 110 fitted to medialcondyle 104 of femur 102 and a tibial prosthetic component 120 fitted tomedial condyle 107 of tibia 101.

Similar prosthetic components may also be fitted to lateral condyle 103and/or lateral condyle 106. Further, the exemplary embodiments belowrefer to prosthetic components on the medial condyles merely forconvenience, and those skilled in the art will appreciate that thedisclosed embodiments apply to prosthetic components on the lateralcondyles as well.

The orientation of femoral prosthetic component 110 and/or tibialprosthetic component 120 may impact the alignment between the tibia 101and the femur 102 and affect how the knee joint 100 articulates. Thus, asurgeon generally determines the proper orientation of femoralprosthetic component 110 and/or tibial prosthetic component 120.Disclosed embodiments provide systems and methods to output orientationsof one or more prosthetic components to the surgeon, such as theorientations of femoral prosthetic component 110 or tibial prostheticcomponent 120. In certain embodiments, the disclosed systems and methodsmay receive input from the surgeon, such as desired looseness ortightness values for the knee joint 100, and may determine theorientations based on this input from the surgeon. The system may useone or more optimization and/or minimization algorithms, discussed ingreater detail below, to determine the orientations.

FIG. 2 is a schematic diagram of an exemplary computer system 200 thatmay be used to determine prosthetic component orientation, consistentwith disclosed embodiments. Computer system 200 may generally beoperable to receive user input 210 corresponding to a desired loosenessof the knee joint and bone position data 220 corresponding to relativepositions of tibia 101 and femur 102. Computer system 200 may also beoperable to output prosthetic component orientations via a display 206Aor other input/output (I/O) devices 206 based on user input 210 and/orbone position data 220. In some embodiments, computer system 200 may beincluded in a computer-assisted surgery system, such as the RIO® RoboticArm Interactive Orthopedic System by MAKO Surgical Corp. of FortLauderdale, Fla., as described, for example, in U.S. patent applicationSer. No. 11/357,197 (U.S. Patent Application Pub. No. 2006/0142657),filed Feb. 21, 2006, which is hereby incorporated by reference herein inits entirety.

As shown in FIG. 2, computer system 200 may include a processor 201, arandom access memory (RAM) module 202, a read-only memory (ROM) module203, a storage device 204, a database 205, I/O devices 206, display206A, and a network interface 207. Processor 201 may include one or moremicroprocessors configured to execute instructions and process data toperform one or more functions associated with computer system 200.Storage device 204 may include a volatile or non-volatile, magnetic,semiconductor, tape, optical, removable, nonremovable, or other type ofstorage device or computer-readable medium. RAM module 202 may includeone or more programs or subprograms loaded from ROM module 203, storagedevice 204, or elsewhere that, when executed by processor 201, performvarious procedures, operations, or processes consistent with disclosedembodiments. For example, RAM module 202 may include one or moreprograms that enable processor 201 to record relative positions of atibia 101 and a femur 102 at a plurality of flexion positions of theknee joint 100 based on position data 220, receive looseness values asuser input 210, determine an orientation of a prosthetic component forthe knee joint 100 based on the recorded relative positions and thelooseness values, and output the orientation information via display206A.

I/O devices 206 may include any devices capable of receiving input froma user and sending output to the user. For example, I/O devices 206 mayinclude a console with an integrated keyboard and mouse to allow a user,e.g., a surgeon, to input parameters such as desired looseness values orany other parameters. I/O devices 206 may also include display 206A thatmay display a graphical user interface (GUI) for outputting andreceiving information. I/O devices 206 may also include peripheraldevices such as, for example, a printer, a user-accessible disk drive(e.g., a USB port, a floppy, CD-ROM, or DVD-ROM drive, etc.), amicrophone, a speaker system, or any other suitable type of interfacedevice. For example, I/O devices 206 may include an electronic interfacethat allows a user to input patient data, such as computed tomography(CT) data into computer system 200 in order to generatethree-dimensional models of the patient's anatomy in software, asdiscussed below.

Database 205 may be included in RAM module 202, ROM module 203, storagedevice 204, or elsewhere. In certain embodiments, database 205 may belocated separately from computer system 200 and may be accessed via anetwork, e.g., by network interface 207. Database 205 may store one ormore three-dimensional models representing various parts of a patient'sanatomy, such as models of all or part of a patient's tibia, femur, kneejoint, etc. These models may be developed, e.g., from data acquiredusing any combination of computed topography (CT), magnetic resonanceimaging (MRI), positron emission tomography (PET), coordinatedfluoroscopy, and angiographic data acquired before and/or duringsurgery. The three-dimensional models stored in database 205 may alsoinclude one or more points about the surface of the models. The pointsmay be selected by a user or may be generated automatically by computersystem 200 or another computer system, and may identify anatomicallandmarks on the three-dimensional models, e.g., the center of a tibialcondyle, a trochlear groove point on the femur, or any other landmarkpoint.

In certain embodiments, the models may be direct representations of apatient's anatomy. For example, in one embodiment, the three-dimensionalmodel may be constructed from a series of pre-operative CT scans takenat cross-sections along a patient's femur 102, knee joint 100, and tibia101. In other embodiments, data points regarding features of thepatient's anatomy may be determined using one or more of theabove-described technologies, or any other technology, and the datapoints may be matched to one or more existing three-dimensional modelsin a library of three-dimensional models that may be stored at database205 or elsewhere.

Database 205 may also store one or more three-dimensional modelscorresponding to one or more prosthetic components. For example,database 205 may include three-dimensional models of different tibialprosthetic components 120 and/or femoral prosthetic components 110.Separate models may be stored based on the manufacturer, model, and sizeof each implant. The models may be generated based on the technicalspecifications of each prosthetic component using computer-aided design(CAD) techniques, or any other technique. Computer system 200 may usethe three-dimensional models of the patient's anatomy and the prostheticcomponents stored in database 205 when determining an orientation of oneor more prosthetic components.

Exemplary features of system 200 will be discussed below with regard toFIGS. 2-5. The disclosure below discusses using system 200 to determinean orientation of the femoral prosthetic component 110 merely forconvenience. Those skilled in the art will appreciate that the methodsand systems described herein may also be used to determine theorientation of tibial prosthetic components 120 and are not limited todetermining the orientation of femoral prosthetic components 110.

Prior to surgery, computer system 200 may use the three-dimensionalmodels of the patient's anatomy and of the prosthetic components storedin database 205 to determine a preliminary orientation of one or moreprosthetic components. For example, prior to surgery, computer system200 may analyze the size, shape, and points identifying anatomicallandmarks of the three-dimensional models to determine a preliminaryorientation of femoral prosthetic component 110 and/or tibial prostheticcomponent 120. In certain embodiments, a surgeon may determine thepreliminary orientation of femoral prosthetic component 110, and maysend the preliminary orientation information to computer system 200,e.g., via one of I/O devices 206. In other embodiments, computer system200 may determine the preliminary orientation of femoral prostheticcomponent 110 without input from a user.

During surgery, the user may interact with computer system 200 to recordrelative positions of femur 102 and tibia 101 at different flexionpositions of knee joint 100. For example, a surgeon may apply avalgus/varus moment (i.e., a lateral force and a bending force) to kneejoint 100 while moving the joint through a range of flexion positions.The valgus/varus moment may attempt to align femur 102 and tibia 101 totheir correct relative positions as they would be in an undiseased,non-arthritic knee. Computer system 200 may record the relativepositions of femur 102 and tibia 101 at the different flexion positionsusing, e.g., coordinated fluoroscopic imagery, or any other method. Thedata related to these relative positions may be stored in database 205or elsewhere within computer system 200.

In some embodiments, the relative positions of femur 102 and tibia 101may be recorded prior to the surgeon resecting the bones and installingthe prosthetic devices. In other embodiments, however, the relativepositions may be recorded after resecting one of the bones andimplanting a prosthetic component. In these embodiments the computersystem 200 may record the relative positions of the non-resected boneand the implanted prosthetic component. For example, if computer system200 is being used to determine an orientation of a femoral prostheticcomponent, the surgeon may resect the damaged area on the tibia andimplant the tibial prosthetic component prior to measuring the relativepositions of the femur and the tibial prosthetic component.

FIG. 3 illustrates a side view of knee joint 100 at multiple differentflexion positions, as may be controlled by a surgeon when recording therelative positions of the femur 102 and the tibia 101, consistent withdisclosed embodiments. As discussed above, the surgeon may manipulatethe patient's leg to place tibia 101 in multiple different flexionpositions such as positions 321, 322, 323, and 324 relative to femur102. For example, position 321 illustrates approximately 90° flexion,position 322 illustrates approximately 60° flexion, position 323illustrates approximately 30° flexion, and position 324 illustratesapproximately 0° flexion or full extension, although any other positionsand number of positions throughout the patient's range of motion may beused.

Computer system 200 may record relative positions of femur 102 and tibia101 (or tibial prosthetic component 120) in each position 321-324. InFIG. 3, tibial prosthetic component 120 has already been installed.Accordingly, in the embodiment of FIG. 3, computer system 200 may recordthe relative positions of femur 102 and tibial prosthetic component 120.However, as discussed above, the relative positions of femur 102 andtibia 101 may be measured prior to resection and implanting tibialprosthetic component 120 and/or femoral prosthetic component 110.

Computer system 200 may record the relative positions of femur 102 andtibia 101 by measuring a distance between a predetermined point, e.g.,one of points 342-345, on tibial prosthetic component 120 and acorresponding point on femur 102 for each flexion position. In oneembodiment, the corresponding point on femur 102 may be a point on thesurface of femur 102 that is closest to the one of points 342-345 beingmeasured at that particular flexion position. Moreover, other methodsmay be used to determine the relative positions of femur 102 and tibia101 (or tibial prosthetic component 120) in each position 321-324, suchas using distances between multiple points, the distance between thepoint on femur 102 and the point on tibia 101 that are closest to eachother, an average distance between curves representing femur 102 andtibia 101, etc.

The location of points 342-345 may be determined, e.g., based on thethree-dimensional models of tibial prosthetic component 120 and/or tibia101. For example, points 342-345 may correspond to anatomical landmarksof tibia 101 that may be stored in database 205, as discussed above.Similarly, points 342-345 may correspond to points on tibial prostheticcomponent 120 or tibia 101 that are located closest to femur 102.

In one embodiment, additional points may be used at certain flexionpositions, such as a flexion position near 90° and a flexion positionnear 0°. For example, computer system 200 may record additional relativeposition data at points 341 for a near-90° flexion position and atpoints 346 for a near-0° flexion position. As shown in FIG. 3, points341 may be located toward a posterior end of tibial prosthetic component120, while points 346 may be located toward an anterior end of tibialprosthetic component 120. Recording relative position data at thesepoints may allow computer system 200 to ensure, e.g., that anorientation of the femoral prosthetic component does not interfere withtibial prosthetic component 120 at certain flexion positions. Thoseskilled in the art will appreciate that the various flexion positionsmentioned herein are approximations that are made, e.g., by the surgeonwhen applying the valgus/varus moment to the knee joint. As such, theactual flexion positions of the knee joint 100 may vary on the order ofseveral degrees.

Once the relative positioning data is collected, this data may be storedat database 205 or elsewhere. The relative positioning data may be usedby computer system 200 in combination with user input to determineorientations for one or more prosthetic components, such as femoralprosthetic component 110, discussed in greater detail below.

As discussed above, computer system 200 may also be configured toreceive desired looseness values from a user, e.g., a surgeon. FIG. 4discloses an exemplary user interface 400 that may be displayed ondisplay 206A, for example, to allow the surgeon to enter the desiredlooseness values. User interface 400 includes three desired loosenessvalue input fields 401, 402, and 403 that allow the surgeon to definedesired looseness values at near-90° flexion, mid-flexion, and near-0°flexion, respectively. For example, the surgeon may enter numericalvalues into input fields 401, 402, and 403, and/or may choose the valuesusing the arrows to the right of each respective input.

As shown in FIG. 4, the looseness values may be entered by the user asdesired separation distances between femoral prosthetic component 110and tibial prosthetic component 120 at different flexion values. Forexample, in user interface 400, the user has selected a 1.5 mm desiredseparation distance at 90° flexion, a 1.5 mm desired separation distanceat mid-flexion (e.g., near-45° flexion), and a 1 mm desired separationdistance at full extension (e.g., near-0° flexion).

Three inputs are shown in FIG. 4. However, in certain embodiments,computer system 200 may generate a user interface with an input fieldfor each flexion position in which a computer system 200 recordedrelative position data of femur 102 and tibia 101 (or tibial prostheticcomponent 120). For example, if a surgeon recorded relative positionsbetween femur 102 and tibia 101 (or tibial prosthetic component 120) atfour different flexion positions, as shown in FIG. 3, the surgeon may beable to enter four desired looseness values, each one corresponding toone of the flexion positions. In another embodiment, the surgeon may belimited to three values. In this embodiment, if the surgeon recordsrelative positions at more than three flexion positions, all but threesets of relative position data may be discarded. For example, computersystem 200 may maintain the sets of relative position data at the threeflexion positions closest to 0°, 45°, and 90° flexion, respectively, andmay discard the other sets of data. Alternatively, relative positiondata from one or more positions in the mid-flexion range, e.g.,positions 322 and 323, may be averaged, interpolated, or otherwisecombined to form a single relative position value close to a mid-flexionpoint, e.g., at near-45° flexion.

User interface 400 may also include “OK” button 405 and “Cancel” button406. When the surgeon is satisfied with the looseness values, thesurgeon may select “OK” button 405. Otherwise the surgeon may select“Cancel” button 406. Selecting “OK” button 405 may send the desiredlooseness values to computer system 200, enabling computer system 200 todetermine a proposed orientation for a prosthetic component based on thedesired looseness values entered by the user and the relative positiondata between femur 102 and tibia 101 (or tibial prosthetic component120) recorded by system 200.

FIG. 5 is a pictorial illustration representing the relative positioningof a three-dimensional femoral prosthetic component model 510 and athree-dimensional tibial prosthetic component model 520 at multipledifferent flexion positions 521-523, consistent with certain disclosedembodiments. Femoral prosthetic component model 510 may be athree-dimensional model for femoral prosthetic component 110, and tibialprosthetic component model 520 may be a three-dimensional model fortibial prosthetic component 120, for example. FIG. 5 illustrates howcomputer system 200 incorporates the three-dimensional models stored,e.g., in database 205, recorded relative position data between femur 102and tibia 101, and the desired looseness values to determine one or moreorientation parameter values of a prosthetic component.

Computer system 200 may determine the location of tibial prostheticcomponent model 520 at near-0° flexion position 521 based on therelative position data recorded at near-0° flexion, discussed above withregard to FIG. 3. Likewise, computer system 200 may determine thelocations of tibial prosthetic component model 520 at near-45° flexionposition 522 and near-90° flexion position 523 based on the relativeposition data recorded at near-45° flexion and near-90° flexion,respectively.

As discussed above with regard to FIG. 3, computer system 200 may recordthe relative position data before or after resection and installation oftibial prosthetic component 520. If computer system 200 records therelative position data after resection and installation, then therecorded position points 531-533 for each position 521-523 maycorrespond to the recorded relative position data that was recordedalong tibial prosthetic component 520 discussed above with regard toFIG. 3. On the other hand, if computer system 200 records the relativeposition data before resection and installation, then computer system200 may calculate the recorded position points 531-533 for each flexionposition 521-523 based on the recorded relative position data recordedalong tibia 101 in FIG. 3, an installation plan for tibial prostheticcomponent 120 (e.g., planned resection depth, etc.), and a known size(e.g., thickness) and shape of tibial prosthetic component 120.

Recorded position points 531-533 may be determined, e.g., based on thethree-dimensional models of tibial prosthetic component 120 and/or tibia101. For example, points 531-533 may correspond to anatomical landmarksof tibia 101 that may be stored in database 205, as discussed above.Similarly, points 531-533 may correspond to points on tibial prostheticcomponent 120 or tibia 101 that are located closest to femur 102. Instill other embodiments, points 531-533 may be determined based on thegeometry of tibial prosthetic component 120, e.g., they may bedetermined to be located at the centroid of tibial component 120, or atsome other position with respect to tibial component 120.

Computer system 200 may also determine target value points 541-543 foreach flexion position 521-523 by adding the desired looseness value foreach flexion position 521-523 to the recorded position points 531-533 ofeach flexion position 521-523. For example, a surgeon may have entered alooseness value of d₁ for near-0° flexion, as discussed above withregard to FIG. 4. Thus, computer system 200 may generate a target valuepoint 541 for near-0° flexion position 521 that is a distance d₁ fromthe recorded position point 531 in a direction substantiallyperpendicular to the surface of tibial prosthetic component model 520 atnear-0° flexion position 521. Likewise, if the surgeon enters desiredlooseness values of d₂ and d₃ for 45° flexion and 90° flexion,respectively, then computer system 200 may similarly generate a targetvalue point 542 d₂ mm from the recorded position point 532 for near-45°flexion position 522 in a direction substantially perpendicular to thesurface of tibial prosthetic component model 520 at near-45° flexionposition 522, and a target value point 543 d₃ mm from the recordedposition point 533 for near-90° flexion position 523 in a directionsubstantially perpendicular to the surface of tibial prostheticcomponent model 520 at near-90° flexion position 523.

Target value points 541-543 generated by computer system 200 maycorrespond to, e.g., a target location for a point on the surface offemoral prosthetic component model 510. Thus, computer system 200 mayimplement one or more algorithms to change the orientation of femoralprosthetic component model 510 in one or more directions and about oneor more axes in order to achieve a close fit between the surface offemoral prosthetic component model 510 and the target value points541-543. For example, computer system 200 may implement one or morealgorithms, examples of which are discussed below, to compare estimatedseparation distance values g₁, g₂, and/or g₃, which may be estimated bycomputer system 200, with their respective desired separation distancevalues d₁, d₂, and/or d₃, in order to minimize separation distanceerrors e₁, e₂, and/or e₃. Based on these algorithms, computer system 200may determine a recommended position and orientation for femoralprosthetic component model 510 relative to a model of the femur, andhence, femoral prosthetic component 110 relative to the femur 102.

In another embodiment, an arbitrary number n of different flexionpositions are collected. The estimated separation distance values g₁,g₂, . . . g_(n) are computed as the minimum distance between thesurfaces of the three-dimensional femoral prosthetic component model 510and the three-dimensional tibia prosthetic component model 520. Theminimum separation distance is an estimate of the physical separationdistance between the femoral and tibial prosthetic components. In thisembodiment, n corresponding distance values d₁, d₂, . . . d_(n) may alsobe entered and/or otherwise collected, and n distance errors e₁, e₂, . .. e_(n) may be calculated as discussed above.

In certain embodiments, computer system 200 may control one or moreorientation parameters to change the orientation of femoral prostheticcomponent model 510 within the sagittal plane. For example, the positionof femoral prosthetic component model 510 in FIG. 5 may correspond tothe preliminary orientation determined by computer system 200 based on,e.g., the edge points and lowpoints of femoral prosthetic componentmodel 510. Computer system 200 may then move femoral prostheticcomponent model 510 in two translational directions substantially withinthe sagittal plane (shown in FIG. 5 as the x-direction and they-direction) by changing an orientation parameter value corresponding toeach direction and may rotate femoral prosthetic component model 510about an axis substantially orthogonal to the sagittal plane (shown inFIG. 5 as θ) by changing an orientation parameter value corresponding tothe rotation about the axis.

In other embodiments, computer system 200 may change the orientation offemoral prosthetic component model 510 within one or more of thesagittal, coronal, and transverse planes. For example, in oneembodiment, computer system 200 may move femoral prosthetic componentmodel 510 in three substantially perpendicular directions (e.g., x-, y-,and z-directions), by changing orientation parameter values for eachdirection, and rotate femoral prosthetic component model 510 about threesubstantially perpendicular axes (e.g., θ-, φ-, and ϕ-rotations), bychanging orientation parameter values for rotation about each axis, soas to be able to orient femoral prosthetic component model 510 in anypossible orientation.

An orientation parameter value may correspond to any type of informationor value capable of determining a one or more aspects of a prostheticcomponent's position or orientation. For example, an orientationparameter value may include a point in a coordinate space, such as atwo-dimensional or a three-dimensional space, or a translational valuealong an axis in the coordinate space. An orientation parameter valuemay also include a rotational value representing rotation about an axis.Moreover, orientation parameter values may include translational and/orrotational differences from a predetermined orientation. For example, anorientation parameter value may represent a difference between apreliminary orientation of a prosthetic component model and an estimatedorientation of the prosthetic component in one or more directions orrotated about one or more axes. The above are merely examples, however,and those skilled in the art will appreciate that orientation parametervalues may be represented in many other ways.

An exemplary algorithm for determining an orientation of femoralprosthetic component model 510 that may be employed by computer system200 includes generating a cost function that includes one or moreorientation parameter values as variable inputs and outputs a cost basedon a difference between one or more estimated separation distances andone or more first desired separation distances, respectively.

In one embodiment, the cost function may be defined as:

$\begin{matrix}{C = {{\sum\limits_{i = 1}^{n}\left( {w_{i}c_{i}} \right)} + c_{x} + c_{y} + c_{\theta}}} & (1)\end{matrix}$where i represents a particular flexion position, n represents the totalnumber of flexion positions that may be collected, w_(i) is a weightingvariable that may be applied for each flexion position, c_(i) is a costfunction for each flexion position, c_(x) is a cost function for movingfemoral prosthetic component model 510 in a first translationaldirection substantially parallel to the sagittal plane (e.g., thex-direction), c_(y) is a cost function for moving prosthetic component510 in a second translational direction substantially parallel to thesagittal plane (e.g., the y-direction), and c_(θ) is a cost function forrotating femoral prosthetic component model 510 about an axissubstantially perpendicular to the sagittal plane (e.g., a θ-rotation).As discussed above, any number n of flexion positions may be collected.Weighting variables w_(i) may allow a user or system controller toweight the relative importance of the separation distance at eachflexion position. In certain embodiments weighting variables w_(i) maybe predetermined. In other embodiments, weighting variables w_(i) may beconfigurable by a user, e.g., a surgeon.

The cost functions of equation (1), c_(i), c_(x), c_(y), and c_(θ), maybe defined as:c _(i) =e _(i), if |e _(i) |≤t _(i)c _(i) =K(e _(i) −t _(i))+t _(i), if |e _(i) |<t _(i)  (2)c _(x)=0, if |Δx|≤t _(x)c _(x) =K(|Δt|−t _(x)), if |Δx|>t _(x)  (3)c _(y)=0, if |Δy|≤t _(y)c _(y) =K(|Δy|−t _(y)), if |Δy|>t _(y)  (4)c _(θ)=0, if |Δθ|≤t _(θ)c _(θ) =K(|Δθ|−t _(θ)), if |Δθ|>t _(θ)  (5)where |e_(i)| represents the absolute value of the difference betweenthe estimated separation distance and the desired separation distancebetween tibial prosthetic component model 520 and femoral prostheticcomponent model 510 at a particular flexion position i (e.g.,|e₁|=|g₁−d₁| as shown in FIG. 5); K represents a constant value; t_(i)represents a separation distance tolerance for a flexion position i, Δx,Δy, and Δθ represent orientation parameter values for the firsttranslational direction substantially parallel to the sagittal plane,the second translational direction substantially parallel to thesagittal plane, and the rotational value about the axis substantiallyperpendicular to the sagittal plane; and t_(x), t_(y), and t_(θ)represent displacement tolerances in each respective direction.

Constant value K may be a large number, e.g., 1,000,000, so as to causea steep cost increase in the cost functions when a separation distanceor a displacement amount exceeds a corresponding threshold value.Tolerance values t_(x), t_(y), and t_(θ) may be determined by a user ormay be predetermined. In one embodiment, t_(x), t_(y), and t_(θ) may beset to 10 mm, 10 mm, and 5°, respectively. Likewise, tolerance valuest_(i) for each flexion position i may be determined by a user or may bepredetermined. In one embodiment, tolerance values t_(i) correspondingto the near-0° and near-90° flexion positions may be set to ±0.25 mm andtolerance values t_(i) corresponding to all other flexion positions maybe set to ±1.00 mm.

While the cost function shown above in equation (1) outputs a cost basedon three potential inputs, namely two translational orientationparameter values and one rotational orientation parameter value, thoseskilled in the art will appreciate that equation (1) can be modified toinclude additional orientation parameter values. For example, equation(1) may be modified to include an additional translational orientationparameter value and two additional rotational orientation parametervalues by adding cost functions c_(z), c_(φ), and c_(ϕ) similar to thecost functions of equations (3)-(5).

Likewise, equation (1) may be modified to include fewer orientationparameter values by removing the respective cost function correspondingto the orientation parameter value(s) to be removed. For example,computer system 200 may modify equation (1) to include only the costfunctions for the x and y translational orientation parameters. In thisembodiment, computer 200 may optimize the x and y translationalorientation parameter values for a given rotational orientationparameter.

As discussed above, the cost function c_(i) for each flexion positiondescribed in equation (2) may include a piecewise equation with twopiecewise portions. In certain embodiments, the cost function c_(i) foreach flexion position may be modified to include a piecewise equationwith more than two piecewise portions. Moreover, the cost function c_(i)may be modified such that the piecewise portions are determined based onthe value of e_(i) rather than the absolute value of e_(i) (e.g.,e₁=g₁−d₁ as shown in FIG. 5). For example, the cost function c_(i) maybe represented as shown in equation (6):c _(i) =K ₁(t _(1,i) −e _(i))+K ₂ t _(1,i), if e _(i) ≤t _(1,i)c _(i) =K ₂(−e _(i)), if t _(1,i) <e _(i)≤0c _(i) =K ₃ e _(i), if 0<e _(i) ≤t _(2,i)c _(i) =K ₄(e _(i) −t _(2,i))+K ₃ t _(2,i), if t _(2,i) <e _(i)  (6)

Constant values K₁ . . . K₄ may be large numbers, e.g., 1,000,000, so asto cause a steep cost increase in the cost functions when a separationdistance or a displacement amount exceeds a corresponding thresholdvalue. In one embodiment, K₁, K₂, K₃, and K₄ may be set to 1,000,000,5,000, 0, and 1,000,000, respectively. Tolerance values t_(1,i), andt_(2,i) may be determined by a user or may be predetermined. In oneembodiment, t_(1,i), and t_(2,i), may be set to −5 mm and 2 mm,respectively.

Equation (6) may be used to determine a cost c_(i) for points at eachflexion position collected. For example, equation (6) may be used todetermine a cost c_(i) for each of points 531-533 shown in FIG. 5, andfor any other points or number of points. For example, in certainembodiments, equation (6) may be used to determine a cost c_(i) at apoint on the anterior tip area of femoral prosthetic component model510. Computer system 200 may use equation (6) to calculate the costc_(i) for each flexion position to be used in conjunction with equation(1), discussed above.

Computer system 200 may implement one or more optimization algorithms todetermine orientation parameter values that minimize the cost functionof equation (1). For example, computer system 200 may apply one or morenonlinear optimization techniques such as the Nelder-Mead simplex searchto determine sets of orientation parameter values that produce one ormore local minima for the cost function of equation (1). Computer system200 may output the sets of orientation parameter values as potentialorientations for femoral prosthetic component model 510.

In certain embodiments, computer system 200 may implement anoptimization algorithm that determines translational parameter valuesthat minimize the cost function of equation (1) for a particularrotational angle θ_(i). Computer system 200 may then rotate femoralprosthetic component model 510 about an axis perpendicular to thesagittal plane by a predetermined increment, and then repeat the processof minimizing the cost function of equation (1) for the new rotationalangle θ_(i+1). Computer system 200 may repeat this process for multipledifferent angles, and may choose the rotational angle θ andcorresponding x and y translational orientation parameter values thatresult in the minimum cost function value as the orientation for femoralprosthetic component model 510, and hence, femoral prosthetic component110.

Another exemplary algorithm for determining an orientation of femoralprosthetic component model 510 (and, hence, femoral prosthetic component110) that may be employed by computer system 200 includes minimizing adifference between one or more desired separation distances andestimated separation distances at one or more flexion positions,respectively. For example, in an embodiment where the relative positionsof femur 102 and tibia 101 are recorded for three different flexionpositions, the exemplary algorithm may move femoral prosthetic componentmodel 510 in the x- and y-directions as shown in FIG. 5, to determinetranslational orientation parameter values in the x- and y-directionsthat minimize values e₁ and e₃, for a particular rotational angle,θ_(i). Computer system 200 may calculate the value of e₂ at thetranslational orientation parameter values in the x- and y-direction forthe particular rotational angle θ_(i). Computer system 200 may thenrotate femoral prosthetic component model 510 by a predeterminedincrement, and then repeat the process of minimizing e₁ and e₃ andmeasuring e₂ for the new rotational angle θ_(i+1). Computer system 200may repeat this process for multiple different angles, and may choosethe rotational angle θ and corresponding x and y translationalorientation parameter values that have the minimum displacement e₂ asthe orientation for femoral prosthetic component model 510, and hence,femoral prosthetic component 110. This algorithm is described in greaterdetail below with respect to FIG. 7.

After computer system 200 has determined the orientation for femoralprosthetic component model 510, and hence, femoral prosthetic component110, it may output the orientation via display device 206A or other I/Odevice 206. For example, computer system 200 may be configured todisplay an image of a femoral prosthetic component model 510 overlayingthree-dimensional model of the patient's femur, and may orient thefemoral prosthetic component model 510 over the patient's femur modelaccording to the orientation information. Moreover, computer system 200may also display information informing the user, e.g., a surgeon, whereto implant the prosthetic component relative to one or morepredetermined markers on the femur. Such information may also include anindication of how much bone to resect to properly orient the femoralprosthetic component, a number, location, and size of holes to form inthe femur in order to secure the femoral prosthetic component, etc.

FIG. 6 is a flowchart illustrating an exemplary process for determiningprosthetic component orientation, consistent with disclosed embodiments.The process may be performed, e.g., by computer system 200. As shown inFIG. 6, computer system 200 may record relative bone positions in theknee joint through a range of motion (step 610). For example, asdiscussed above, a surgeon may apply a valgus/varus moment to the kneejoint 100 and computer system 200 may record the relative positionsbetween the femur 102 and the tibia 101 (or tibial prosthetic component120) at one or more flexion positions through the patient's range ofmotion.

Computer system 200 may also receive desired looseness values from theuser, e.g., the surgeon (step 620). In some embodiments, the loosenessvalues may be expressed as a desired separation distance between afemoral prosthetic component 110 and a tibial prosthetic component 120at one or more flexion positions of the knee joint 100.

Computer system 200 may then determine target values based on therecorded bone positions and the received desired looseness values (step630). For example, computer system 200 may modify the recorded bonepositions based on the received desired looseness values to determinethe target values. The target values may correspond to, e.g., a targetlocation for a point on the surface of a prosthetic component.

Computer system 200 may also calculate at least one orientationparameter value based on the target values (step 640). For example, asdiscussed above, computer system 200 may implement one or morealgorithms to calculate at least one orientation parameter value for theprosthetic component. In some embodiments, computer system 200 maycalculate three or more orientation parameter values. If computer system200 calculates three orientation parameter values, those parametervalues may include two translational orientation parameter values andone rotational orientation parameter value that specify an orientationof the prosthetic component in the sagittal plane. In certainembodiments, computer system 200 may implement one or more algorithms tocalculate orientation parameter values such that a cost function, e.g.,as shown in equation (1) is minimized.

Computer system 200 may output the at least one orientation parametervalue to the user (step 650). For example, computer system 200 mayoutput the orientation parameter value to the user as a numerical value,e.g., a translational distance by which to move the prostheticcomponent. In other embodiments, computer system 200 may output one ormore orientation parameter values as an image of the three-dimensionalmodel for the femoral prosthetic component 110 overlaying thethree-dimensional model of the patient's femur, and may orient thefemoral prosthetic component model 510 over the patient's femur modelaccording to the orientation information.

FIG. 7 is a flowchart illustrating an exemplary process for determiningprosthetic component orientation, consistent with disclosed embodiments.The process may be performed by computer system 200, e.g., as a part ofstep 640 in FIG. 6. For example, FIG. 7 illustrates a process fordetermining prosthetic component orientation by minimizing differencesbetween desired separation distances and estimated separation distancesbetween a femoral prosthetic component 110 and a tibial prostheticcomponent 120 at two different flexion positions. As discussed above,computer system 200 may perform such calculations using, e.g., one ormore three-dimensional models, such as three-dimensional models 510 and520 of FIG. 5. In one embodiment, the two different flexion positionsmay be a near-0° flexion position and a near-90° flexion position,although other flexion positions may be used.

Computer system 200 may initialize a rotational orientation parametervalue θ_(i) to a predetermined value, θ_(start) (step 710). In oneembodiment, θ_(start) may be set to −5°, although any value may be used.

Computer system 200 then determines the x and y translationalorientation parameter values that minimize the squares of a difference,e₁, between a desired separation distance d_(i) and an estimatedseparation distance g₁ for a first flexion position, and a difference,e₃, between a desired separation distance d₃ and an estimated separationdistance g₃ for a third flexion position (step 720). For example,computer system 200 may use any type of optimization technique, such asany combination of linear or non-linear optimization, curve fittinganalysis, regression analysis, etc., to minimize e₁ and e₃.

Computer system 200 may then calculate the square of the difference, e₂,between a desired separation distance and an estimated separationdistance for a second flexion position at the x and y translationalorientation parameter values determined in step 720 (step 730). In oneembodiment, e₁ may be determined at a near-0° flexion position, e₃ maybe determined at a near-90° flexion position, and e₂ may be determinedat some flexion position in between 0° and 90°.

Computer system 200 may then determine if the current rotationalorientation parameter value θ_(i) is greater than or equal to apredetermined value θ_(end) (step 740). In one embodiment, θ_(end) maybe set to 5°, although any value may be used. If computer system 200determines that θ_(i) is not greater than or equal to a predeterminedvalue θ_(end) (step 740, N), computer system 200 may increment θ_(i) by1°, e.g. may rotate femoral prosthetic component model 510 by 1° (step750) and return to step 720, wherein steps 720-750 repeat until θ_(i) isgreater than or equal to a predetermined value θ_(end). Of course, θ_(i)can be incremented by any other value, such as 0.25°, 0.5°, 2°, etc.

If, on the other hand, computer system 200 determines that θ_(i) isgreater than or equal to a predetermined value θ_(end) (step 740, Y),computer system 200 may determine which one of the θ_(i) values has theminimum corresponding (e₂)² value (step 760).

Computer system 200 may then determine whether the minimum corresponding(e₂)² value from step 760 satisfies one or more requirements, such asbeing equal to a predetermined minimum or tolerance value, or whether amaximum number of iterations have been reached (step 770). If theminimum corresponding (e₂)² value is not equal to or less than apredetermined minimum or tolerance value and if the maximum number ofiterations have not been reached (step 770, N), then the process returnsto step 710 where another iteration is performed. If another iterationis performed, computer system 200 may use one or more learning orgenetic algorithms to choose different values for the x and ytranslational orientation parameter values for each θ_(i) in asubsequent iteration, so as to converge on x and y translationalorientation parameter values that result in an (e₂)² value less than athreshold or minimum value. The predetermined minimum or tolerance valuein step 770 may or may not be customizable by a user. In one embodimentthe predetermined minimum or tolerance value may be set to 0.5 mm.Likewise the maximum iterations value may or may not be customizable bya user. In one embodiment the maximum iterations value may be set to 50iterations.

If, on the other hand, computer system 200 determines that thecorresponding (e₂)² value is equal to or less than a predeterminedminimum or tolerance value, or a maximum number of iterations have beenreached (step 770, Y), then computer system 200 may output the θ_(i)rotational orientation parameter value and the x and y translationalorientation parameter values that correspond to the (e₂)² value (step780).

Systems and methods described herein provide a solution for determiningan orientation for one or more prosthetic components to be used in asurgery such as an unicompartmental arthroplasty. Presently disclosedmethods and systems may have several advantages. For example, systemsand methods may allow a user, such as a surgeon, to enter desiredlooseness values for a knee joint and receive suggestions fororientations of one or more prosthetic components based on the desiredlooseness values. Thus, the methods and systems may save the surgeontime and effort, resulting in shorter surgery times and lesspre-operative planning time on the surgeon's part. Moreover, the methodsand systems may facilitate proper orientation of one or more prostheticcomponents, resulting in proper knee joint articulation, which may inturn increase the life expectancy of the prosthetic components.

The foregoing descriptions have been presented for purposes ofillustration and description. They are not exhaustive and do not limitthe disclosed embodiments to the precise form disclosed. Modificationsand variations are possible in light of the above teachings or may beacquired from practicing the disclosed embodiments. For example, thedescribed implementation includes software, but the disclosedembodiments may be implemented as a combination of hardware and softwareor in firmware. Examples of hardware include computing or processingsystems, including personal computers, servers, laptops, mainframes,microprocessors, and the like. Additionally, although disclosed aspectsare described as being stored in a memory, one skilled in the art willappreciate that these aspects can also be stored on other types ofcomputer-readable storage devices, such as secondary storage devices,like hard disks, floppy disks, a CD-ROM, USB media, DVD, or other formsof RAM or ROM.

Other embodiments will be apparent to those skilled in the art fromconsideration of the specification and practice of the embodimentsdisclosed herein. The recitations in the claims are to be interpretedbroadly based on the language employed in the claims and not limited toexamples described in the present specification or during theprosecution of the application, which examples are to be construednon-exclusively. Further, the steps of the disclosed methods may bemodified in any manner, including by reordering, combining, separating,inserting, and/or deleting steps. It is intended, therefore, that thespecification and examples be considered as exemplary only, with a truescope and spirit being indicated by the following claims and their fullscope equivalents.

What is claimed is:
 1. A computer-implemented method for determining anorientation parameter value of a prosthetic component, the methodcomprising: using a virtual model of a knee joint comprising a femur anda tibia and a virtual model of a first prosthetic component to determinea planned preliminary orientation of the first prosthetic component inthe knee joint, wherein the first prosthetic component is one of afemoral prosthetic component or a tibial prosthetic component;receiving, at an input device coupled to a processor, an input from auser descriptive of a first desired separation distance between thefirst prosthetic component and a second prosthetic component at a firstflexion position of the knee joint, wherein the second prostheticcomponent is the other of a femoral prosthetic component or a tibialprosthetic component; determining, using a tracking or imaging system,relative positions of the femur and the tibia at a plurality of flexionpositions of the knee joint; recording, by the processor, positionaldata of the tibia and the femur determined using the tracking or imagingsystem when the knee joint is in the first flexion position; estimating,based on the positional data, a first estimated separation distancebetween the first prosthetic component and the second prostheticcomponent at the first flexion position of the knee joint for at leastone potential orientation of the first prosthetic component; determininga first error value as the different between the first desiredseparation distance and the first estimated separation distance;determining a first orientation parameter value of the first prostheticcomponent that minimizes the first error value; displaying, on adisplay, the first orientation parameter value; moving the virtual modelof the first prosthetic component in the model of the knee jointaccording to the first orientation parameter value to update the plannedpreliminary orientation of the first prosthetic component; and providingto the user a location for implanting the first prosthetic component onthe associated femur or tibia according to the first orientationparameter value.
 2. The computer-implemented method of claim 1, furthercomprising: receiving a second desired separation distance between thefirst prosthetic component and the second prosthetic component at asecond flexion position of the knee joint; receiving a third desiredseparation distance between the first prosthetic component and thesecond prosthetic component at a third flexion position of the kneejoint; estimating a second estimated separation distance between thefirst prosthetic component and the second prosthetic component at thesecond flexion position of the knee joint for the at least one potentialorientation of the femoral prosthetic component; estimating a thirdestimated separation distance between the first prosthetic component andthe second prosthetic component at the third flexion position of theknee joint for the at least one potential orientation of the firstprosthetic component determining a second and a third error value as thedifference between the second and third estimated separation distancesto the second and third desired separation distances, respectively; anddetermining the first orientation parameter value that minimizes atleast one of the first, second, or third error values.
 3. Thecomputer-implemented method of claim 2, further comprising: determininga second orientation parameter value and a third orientation parametervalue of the first prosthetic component that minimizes the second errorvalue and the third error value, respectively.
 4. Thecomputer-implemented method of claim 3, wherein the first orientationparameter value and the second orientation parameter value eachrepresents a translation along an axis in a sagittal plane, and thethird orientation parameter value represents a rotation about an axissubstantially perpendicular to the sagittal plane.
 5. Thecomputer-implemented method of claim 4, further including: determiningfourth, fifth, and sixth orientation parameter values that minimizes thefirst, second, and third error values, respectively, wherein the fourthorientation parameter value represents a translation along an axissubstantially perpendicular to the sagittal plane, the fifth orientationparameter value represents a rotation about an axis substantiallyperpendicular to a coronal plane, and the sixth orientation parametervalue represents a rotation about an axis substantially perpendicular toa transverse plane.
 6. The computer-implemented method of claim 2,further comprising: determining a second orientation parameter value,wherein determining the first orientation parameter value and the secondorientation parameter value of the first prosthetic component furtherincludes: generating a cost function that includes, as first and secondinputs, the first and second orientation parameter values, respectively,and that has a cost based on both a difference between the firstestimated separation distance and the first desired separation distanceand a difference between the second estimated separation distance andthe second desired separation distance; determining a local minimum forthe cost function; and determining the first and second orientationparameter values to be the values of the first and second inputs at thelocal minimum of the cost function.
 7. The computer-implemented methodof claim 3, wherein determining the first, second, and third orientationparameter values of the first prosthetic component further include:generating a cost function that includes, as first, second, and thirdinputs, the first, second, and third orientation parameter values,respectively, and that has a cost based on a difference between thefirst estimated separation distance and the first desired separationdistance, a difference between the second estimated separation distanceand the second desired separation distance, and a difference between thethird estimated separation distance and the third desired separationdistance; determining a local minimum for the cost function; anddetermining the first, second, and third orientation parameter values tobe the values of the first, second, and third inputs at the localminimum of the cost function.
 8. The computer-implemented method ofclaim 4, wherein determining the first, second, and third orientationparameter values of the first prosthetic component further include: foreach of a plurality of potential third orientation parameter values:determining a potential first orientation parameter value and apotential second orientation parameter value so as to minimize adifference between the first estimated separation distance and the firstdesired separation distance and so as to minimize a difference betweenthe third estimated separation distance and the third desired separationdistance; and calculating a difference between the estimated secondseparation distance and the desired second separation distance;comparing the calculated difference between the estimated secondseparation distance and the desired second separation distance for eachof the plurality of potential third orientation parameter values todetermine the potential third orientation parameter value correspondingto the smallest calculated difference; and determining that thepotential third orientation parameter value and its correspondingpotential first and second orientation parameter values that correspondto the smallest calculated difference are the first, second, and thirdorientation parameter values, if the smallest calculated difference isless than a threshold difference.
 9. The computer-implemented method ofclaim 1, wherein the first prosthetic component is one of a medial orlateral unicompartmental femoral implant.
 10. The computer-implementmethod of claim 2, wherein determining the first orientation parametervalue comprises: selecting a preferred error value to minimize out ofthe first, second, and third error value; and determining the firstorientation parameter that minimizes the preferred error value.
 11. Asystem for determining an orientation parameter value of a prostheticcomponent, the system comprising: an input device configured to receivea first desired separation distance between a tibial prostheticcomponent and a femoral prosthetic component at a first flexion positionof a knee joint comprising a femur and a tibia; a tracking or imagingsystem configured to determine relative positions of the femur and thetibia at a plurality of flexion positions of the knee joint; aprocessor, operatively coupled to the input device and configured to:determine a planned preliminary orientation of a first prostheticcomponent in the knee joint using a virtual model of the knee joint anda virtual model of the first prosthetic component, wherein the firstprosthetic component is one of a femoral prosthetic component or atibial prosthetic component; record positional data of the tibia and thefemur determined using the tracking or imaging system when the kneejoint is in the first flexion position; estimate, based on thepositional data, a first estimated separation distance between the firstprosthetic component and a second prosthetic component at the firstflexion position of the knee joint for at least one potentialorientation of the first prosthetic component, wherein the secondprosthetic component is the other of a femoral prosthetic component or atibial prosthetic component; and determine a first error value as thedifference between the first desired separation distance and the firstestimated separation distance; determine a first orientation parametervalue of the first prosthetic component that minimizes the first errorvalue; and a display operatively coupled to the processor and configuredto output the first orientation parameter value; and wherein theprocessor is further configured to move the virtual model of the firstprosthetic component in the virtual model of the knee joint according tothe first orientation parameter value to update the planned preliminaryorientation of the first prosthetic component; and wherein the processoris further configured to provide to a user a location for implanting thefirst prosthetic component on the associated femur or tibia according tothe first orientation parameter value.
 12. The system of claim 11,wherein the input device is further configured to: receive a seconddesired separation distance between the first prosthetic component andthe second prosthetic component at a second flexion position of the kneejoint; and receive a third desired separation distance between the firstprosthetic component and the second prosthetic component at a thirdflexion position of the knee joint; and the processor is furtherconfigured to: estimate a second estimated separation distance betweenthe first prosthetic component and the second prosthetic component atthe second flexion position of the knee joint for the at least onepotential orientation of the first prosthetic component; and estimate athird estimated separation distance between the first prostheticcomponent and the second prosthetic component at the third flexionposition of the knee joint for the at least one potential orientation ofthe first prosthetic component determine a second and a third errorvalue as the difference between the second and third estimatedseparation distances to the second and third desired separationdistances, respectively; and determine the first orientation parametervalue that minimizes at least one of the first, second, or third errorvalues.
 13. The system of claim 12, wherein the processor is furtherconfigured to: determine a second orientation parameter value and athird orientation parameter value of the first prosthetic component thatminimizes the second error value and the third error value,respectively.
 14. The system of claim 13, wherein the first orientationparameter value and the second orientation parameter value eachrepresents a translation along an axis substantially in a sagittalplane, and the third orientation parameter value represents a rotationabout an axis substantially perpendicular to the sagittal plane.
 15. Thesystem of claim 13, wherein the processor is further configured to:generate a cost function that includes, as first, second, and thirdinputs, the first, second, and third orientation parameter values,respectively, and that has a cost based on a difference between thefirst estimated separation distance and the first desired separationdistance, a difference between the second estimated separation distanceand the second desired separation distance, and a difference between thethird estimated separation distance and the third desired separationdistance; determine a local minimum for the cost function; and determinethe first, second, and third orientation parameter values to be thevalues of the first, second, and third inputs at the local minimum ofthe cost function.
 16. The system of claim 14, wherein the processor isfurther configured to, for each of a plurality of potential thirdorientation parameter values: determine a potential first orientationparameter value and a potential second orientation parameter value so asto minimize a difference between the first estimated separation distanceand the first desired separation distance and so as to minimize adifference between the third estimated separation distance and the thirddesired separation distance; calculate a difference between theestimated second separation distance and the desired second separationdistance; compare the calculated difference between the estimated secondseparation distance and the desired second separation distance for eachof the plurality of potential third orientation parameter values todetermine the potential third orientation parameter value correspondingto the smallest calculated difference; and determine that the potentialthird orientation parameter value and its corresponding potential firstand second orientation parameter values that correspond to the smallestcalculated difference are the first, second, and third orientationparameter values, if the smallest calculated difference is less than athreshold difference.
 17. The system of claim 12, wherein the processoris further configured to: select a preferred error value to minimize outof the first, second, and third error value; and determine the firstorientation parameter that minimizes the preferred error value.
 18. Acomputer-implemented method for determining an orientation of aprosthetic component, the method comprising: determining, by a processorassociated with a computer, a planned preliminary orientation of a firstprosthetic component in a knee joint using a virtual model of the kneejoint comprising a femur and a tibia, and a virtual model of the femoralprosthetic component, wherein the first prosthetic component is one of afemoral prosthetic component or a tibial prosthetic component;determining, using a tracking or imaging system, relative positions ofthe femur and the tibia at a plurality of flexion positions of the kneejoint; recording, by a processor associated with a computer, relativepositions of the tibia and the femur at the plurality of flexionpositions determined using the tracking or imaging system; receiving,from a user via a user interface, a plurality of looseness values, eachof the plurality of looseness values corresponding to a loosenesspreference between the first prosthetic component and a secondprosthetic component for one of the plurality of flexion positions ofthe knee, wherein the second prosthetic component is the other of afemoral prosthetic component or a tibial prosthetic component;determining a first error value based on the recorded relative positionsof the tibia and the femur, and the received looseness values; determinean orientation of the first prosthetic component that minimizes thefirst error value; displaying, on a display, the orientation of thefirst prosthetic component; moving the virtual model of the firstprosthetic component in the model of the knee joint according to thedetermined orientation to update the planned preliminary orientation ofthe first prosthetic component; and providing to the user a location forimplanting the first prosthetic component on the associated femur ortibia according to the determined orientation.
 19. Thecomputer-implemented method of claim 18, wherein determining theorientation of the prosthetic component includes: determining targetvalue points based on the recorded relative positions of the tibia andthe femur and the received looseness values; and modifying anorientation of the model of the first prosthetic component to minimize adistance between the target points and a surface of the model of thefirst prosthetic component.
 20. The computer-implemented method of claim18, wherein the orientation of the first component includes twotranslational values each along an axis substantially in the sagittalplane, and a rotational value about an axis substantially perpendicularto the sagittal plane.